The opioid crisis has been a perplexing issue, baffling scientists for nearly two decades as they have strived to comprehend the ever-changing societal and systemic reasons that induce people to misuse opioids and to pinpoint prospective overdose danger zones.
These painstaking and frequently imperfect endeavors unfold as healthcare providers endeavor to deliver secure, efficient therapy, and other resources to those grappling with addiction.
As both scientists and healthcare providers scrutinize the expansive and enduring influence of the opioid crisis, they are now inquisitively investigating AI (Artificial Intelligence) and pondering, Could AI be the key to ending the opioid crisis?
Tech Adoption in Healthcare: A Slow Process
Healthcare is not a sector known for swiftly adopting new trends; it’s notoriously slow in testing and incorporating novel technology. This hesitance has its repercussions. One study implies that the industry forfeits over $8.3 billion annually because of its reluctance or failure to adopt technology such as sophisticated electronic health records.
Public health scientists and biomedical engineers have been discreetly fostering an AI-driven revolution in medicine, with addiction prevention and treatment being the latest beneficiaries.
However, the costs of the opioid crisis extend beyond financial losses. Since 1999, over 1 million people have perished due to drug-related overdoses. In 2021, 106,699 drug overdose deaths were recorded in America, marking one of the highest per capita volumes in the nation’s history. Approximately 75% of all these overdoses were linked to opioid use, which includes prescribed analgesics such as Vicodin and Percocet, along with illicit drugs like heroin.
Despite the Centers for Disease Control and Prevention and the National Institutes of Health investing billions of dollars into outreach, education, and prescription monitoring programs, the crisis has stubbornly persisted.
The Opioid Crisis: The Human Cost
For the past decade, I have been conducting research on the opioid crisis in rural and urban communities across America, including New York City and rural southern Illinois.
Most of my peers concur, albeit reluctantly, that there’s a considerable amount of speculation involved in pinpointing the complex risks faced by drug users. Which drugs will they acquire? Will they inject, snort, or smoke them? Who, if anyone, will they use around, in case they overdose and require assistance?
But that’s not all. Practitioners also regularly grapple with inconsistent federal and state guidelines on effective treatments for opioid use disorder, like suboxone. They also find themselves playing catch-up with increasingly unpredictable drug supplies contaminated with affordable, synthetic opioids like fentanyl, which is largely responsible for recent surges in opioid-related overdose deaths.
While AI advancements like ChatGPT have captured most of the public’s imagination, public health researchers and biomedical engineers have been quietly brewing an AI-infused revolution in medicine, with addiction prevention and treatment being the newest recipients.
AI Innovations in Opioid Crisis Management
Innovations in this space primarily utilize machine learning to identify individuals who may be at risk of developing opioid use disorder, disengaging from treatment, and relapse. For instance, researchers from the Georgia Institute of Technology recently developed machine-learning techniques to effectively identify individuals on Reddit who were at risk of fentanyl misuse, while other researchers developed a tool for locating misinformation about treatments for opioid use disorder, both of which could allow peers and advocates to intervene with education.
Other AI-powered programs, such as Sobergrid, are developing the capacity to detect when individuals are at risk of relapsing — for example, based on their proximity to bars — then connecting them to a recovery counselor.
The most impactful advancements relate to the reduction of overdoses, often triggered by drug mixing. At Purdue University, researchers have developed and piloted a wearable device that can detect signs of overdose and automatically inject an individual with naloxone, an overdose-reversing agent. Another significant development has been the creation of tools to detect hazardous contaminants in drug supplies, which could drastically reduce fentanyl-driven overdoses.
The Potential Pitfalls of AI in Opioid Crisis Management
Despite the immense potential, there are concerns — could facial recognition technology be used to locate people who appear intoxicated, leading to discrimination and abuse? Uber has already taken a step in developing this kind of capacity in 2008, attempting to patent a technology that would detect a drunk passenger.
And what about dis/misinformation, a problem already plaguing chatbots? Might malicious parties embed incorrect information into chatbots to mislead drug users about risks?
The Fine Balance
Since Fritz Lang’s seminal silent film “Metropolis” in 1927, the public has been fascinated by the idea of new, humanlike technology making lives easier and richer. From Stanley Kubrick’s “2001: A Space Odyssey” in 1968 to films like “I, Robot” and “Minority Report” in the early 2000s, though, these hopeful visions have slowly morphed into a kind of existential dread.
It will be up to not just researchers and clinicians, but also patients and the broader public to keep AI honest and prevent humanity’s biggest challenges, like the opioid crisis, from becoming insurmountable ones.
